PROJECT SUMMARY Glycosphingolipids (GSL) are essential components of all biological membranes and serve as receptors and modulators of cell-cell and cell-pathogen interactions as well as regulators of diverse receptor-mediated cell signaling events. Highly sensitive, rapid, and facile methods for analyzing GSL structures harvested from biological sources do not currently exist, but would catalyze broader participation by non-glycoscientists in understanding GSL function. Most current glycomics approaches for the characterization of GSL structure utilize enzymatic digestion to release the hydrophilic glycan from the hydrophobic lipid. While this approach simplifies the complexity of the analyte, it blinds the analyst from detecting lipid heterogeneity and, thereby, ignores the biological importance of the lipid portion of the GSLs. Furthermore, enzyme-substrate preferences bias glycan profiles generated by digestion. Liquid chromatography (LC) of released GSL glycans coupled to mass spectrometry (MS) have been broadly applied to quantifying and characterizing GSL profiles. Unfortunately, LC-MS based analytic approaches are not able to profile both neutral and acidic GSL components at the same time and these workflows generally require time-consuming sample preparation and intensive manual interpretation of the data. To remedy the consequences of enzyme bias and chromatographic complexity, we will develop, a sensitive, robust and comprehensive methodology for glycosphingolipidomics supported by a semi-automated annotation software with a highly-curated database to further understand the biological significances of GSLs. We propose to develop standardized methods for the preparation and identification of intact GSL without using enzymatic release of the glycan from the lipid portion. Furthermore, these methods will employ permethylation to enhance structural analysis and to support the simultaneous identification of neutral and acidic GSL structures. As part of the proposed workflow we will optimize this method for different MS analytical platforms and fragmentation types. The sample preparation and MS methods will be complimented by a software suite that facilitates analysis and annotation of the resulting datasets. The software will support high throughput MS data analysis by significantly reducing the time required for annotation and interpretation. Sample preparation protocols as well as MS methods for different platforms and fragmentation types will be made publicly available to the community on our project website. The software will be freely available for download as well.